1 intro

1.1 Purpose

  1. Validate trialwise ub55 Stroop GLM high-vs-low contrast.
  2. Explore methods of modeling trial-wise parcel-mean beta estimates.

1.2 Notes on analyses

GLMs

  • DMCC55B
  • trialwise LS-A, fix-shaped BLOCK(1,1), Stroop

Contrasts (on regional means):

  • Stroop: \((\text{PC50InCon} + \text{biasInCon} - \text{PC50Con} - \text{biasCon})/2\)

Plotting and statistical details:

2 quick look

2.1 raw data

3 prelim models

3.1 Brains: group-level t-statistics

  • t-values displayed; from HLM fitted to trial-level data (see intro)
  • colors are reversed (black = high, yellow = low) so large positive effects can be seen on white underlay.

3.1.1 Stroop effect: bias stimuli

3.1.2 Stroop effect: PC50 stimuli

3.1.3 Stroop effect: bias+PC50

3.1.4 bias effect: bias - PC50

4 trimmed models

4.1 model QC: outliers

4.2 comparison of effect sizes to untrimmed model

4.3 Examining between-subject variance in stroop (hi/lo) contrast

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4.4 Brains: between-subject variance in stroop (hi/lo) contrast

  • standar deviations of level-two stroop contrasts displayed; from HLM fitted to trial-level data (see intro)
  • colors are reversed (black = high, yellow = low) so large positive effects can be seen on white underlay.

4.4.1 Stroop effect: bias+PC50

5 crossed random effects: subject*item

6 comparison to runwise 1trpk models

6.1 difference maps

6.2 t-stats